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import gradio
import nltk
import pandas as pd
from transformers import pipeline
summarizer = pipeline('summarization', model='t5-base')
# classifier_model_name = 'bhadresh-savani/distilbert-base-uncased-emotion'
# classifier_emotions = ['anger', 'disgust', 'fear', 'joy', 'sadness', 'surprise']
classifier_model_name = 'ProsusAI/finbert'
classifier_emotions = ['positive', 'neutral', 'negative']
classifier = pipeline('text-classification', model=classifier_model_name)
def my_inference_function(name):
return "Hello " + name + "!"
gr_interface = gradio.Interface(
fn = my_inference_function,
inputs = "text",
outputs = "text"
)
gr_interface.launch()
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